m11.2

d<-Book%>%dplyr::select(Included2017, ADG,ADF,BW_start)
d<-d[complete.cases(d), ]
d$Included2017<-as.factor(d$Included2017)
levels(d$Included2017)<-list("1"="Yes", "0"="No")
fit<-glm(Included2017~ADF*ADG + BW_start, 
         data=d, 
         family="binomial",x=TRUE, y=TRUE)

d$Included2017<-as.numeric(d$Included2017-1)
m11.2 <- quap(
  alist(
    Included2017 ~ dbinom( 1 , p ) ,
    logit(p) <- a + b*ADG + c*ADF + d*ADG*ADF + e*BW_start ,
    a ~ dnorm( -30  , 10  ),
    b ~ dnorm( 0.3  , 0.5 ),
    c ~ dnorm( 0.4  , 0.5 ),
    d ~ dnorm( 0.06 , 0.5 ),
    e ~ dnorm( 0    , 0.5 )
  ) , data=d )
set.seed(1999)
prior <- extract.prior( m11.2 , n=1e4 )
precis(m11.2, depth=2)
plot(precis(m11.2, depth=2))